Fullstory Added Agentic Review Capabilities to Platform
The new suite enables AI agents to autonomously investigate user behavior data for faster technical resolution.
Updated on Sept. 29, 2026 in Artificial Intelligence
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Fullstory has released Fullstory MCP and StoryAI Agents, allowing AI coding tools to directly access and analyze live behavioral session data. These tools are designed to automate the identification of user experience issues and process stalls.
Why it matters
By integrating session context directly into development environments, the update aims to accelerate debugging by bridging the gap between error reporting and actual user interaction. It allows automated agents to move beyond static code logs to diagnose front-end performance.
The Agentic Session Review tool provides agents with a specific suite of functions including review-open, review-zoom, and review-snapshot to navigate semantic event maps. This allows agents to compare application state across specific timestamps rather than relying on generalized error logs.
The players
Fullstory
A digital experience intelligence platform that captures behavioral data for web and mobile applications.
The details
The system works by providing AI tools with live behavioral context via the Fullstory MCP (Model Context Protocol). Agentic Session Review enables AI coding agents to access production sessions from a terminal, allowing them to perform autonomous data retrieval and analyze process stalls. The platform update also includes enhanced mobile support for Flutter and Compose Multi-Platform, providing auto-generated selectors to help agents identify user interface elements during automated reviews.
Timeline
September 29, 2026: Fullstory announced the release of new product capabilities.
The Tech Race
This release follows the industry trend of connecting AI agents to real-time, domain-specific data via the Model Context Protocol. It positions Fullstory against existing logging tools by moving from passive monitoring to active, agent-driven session analysis.
Enterprise teams using Sentry, Datadog, or Segment can now link session data directly into their existing diagnostic workflows. Developers will first need to integrate the new Agent-Native Toolset to allow their AI coding agents to access live session state from the terminal.
The takeaway
The move suggests a shift toward autonomous debugging where AI agents proactively surface user-facing issues before they are manually triaged. Users should watch for performance benchmarks regarding how many session-based errors these agents can resolve without human intervention.
Further reading
Explore the latest developments in agentic tooling within our Artificial Intelligence section.
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Do you trust autonomous AI agents to manage and resolve complex technical issues without human intervention?
